Associate - Data Science / Applied AI ML

Vibehackers; Hinoba-an; On-site; PHP 1,200,000 - 2,100,000; Full time

Job summary

Vibehackers is seeking an Associate to design and build AI-powered applications leveraging LLMs, LangGraph/LangChain, and agentic workflows for enterprise environments. You will develop scalable Python services, RAG/Knowledge Graph solutions, and secure integrations across data sources, APIs, and business users.

You will collaborate with Compliance, Technology, and Business stakeholders to translate AI outputs into actionable insights, create dashboards, and contribute to reusable frameworks and

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related quantitative field.
• 5+ years of experience developing software, automation, analytics, or AI solutions.
• Strong programming skills in Python and SQL.
• Experience working with LLMs, Generative AI platforms, prompt engineering, and AI application development.
• Experience building solutions with orchestration frameworks such as LangGraph or LangChain (or similar).
• Understanding of Agentic AI concepts including tool calling, workflow automation, memory management, and multi-step reasoning.
• Experience implementing MCP (Model Context Protocol) integrations or similar enterprise integration patterns.
• Familiarity with RAG, embeddings, vector databases, semantic search, and knowledge retrieval techniques.
• Experience integrating with REST APIs and working with JSON.
• Strong problem-solving, analytical, and communication skills; ability to work independently and collaboratively.

Responsibilities

• Design and implement AI agents and multi-step agentic workflows that integrate with enterprise systems and APIs.
• Build orchestration workflows using frameworks such as LangGraph, Semantic Kernel, LangChain, or similar technologies.
• Implement MCP (Model Context Protocol) or equivalent integrations to securely connect AI applications to enterprise systems and knowledge sources.
• Develop Retrieval-Augmented Generation (RAG), GraphRAG, and Knowledge Graph solutions for knowledge retrieval and semantic search.
• Develop scalable Python applications, APIs, and services to support AI and analytics use cases; work with SQL for data access.
• Perform data exploration, experimentation, testing, and performance optimization over structured and unstructured datasets.
• Create dashboards and reporting solutions to translate AI outputs into stakeholder-facing insights.
• Collaborate with Compliance, Technology, and Business stakeholders; contribute to reusable frameworks, engineering standards, testing practices, and AI governance.

Skills

Python

SQL

LLMs & Generative AI

Prompt Engineering

AI Governance

Analytical Thinking

Communication

Team Collaboration

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

LangGraph

LangChain

Semantic Kernel

MCP (Model Context Protocol)

GraphRAG

Neo4j

REST APIs

JSON

Job description

Associate - Data Science / Applied AI ML

Directly involves building with LLMs, LangChain/LangGraph, RAG, and agentic workflows — very aligned with vibe coding and rapid AI-assisted prototyping.

About the Role

Build and integrate AI-powered applications and agentic systems for enterprise workflows, leveraging LLMs, generative AI, orchestration frameworks, and knowledge retrieval techniques. Develop scalable Python services, RAG/Knowledge Graph solutions, and secure integrations across data sources, APIs, and business stakeholders.

Job Description

Role

Associate role focused on developing AI-powered applications that use LLMs, Generative AI, and Agentic AI to interact with enterprise tools, data sources, APIs, and business workflows. The role emphasizes building orchestration workflows, secure model integrations, retrieval-augmented solutions, and scalable Python-based services that turn AI outputs into actionable business insights.

Key Responsibilities

• Design and implement AI agents and multi-step agentic workflows that integrate with enterprise systems and APIs.
• Build orchestration workflows using frameworks such as LangGraph, Semantic Kernel, LangChain, or similar technologies.
• Implement MCP (Model Context Protocol) or equivalent integrations to securely connect AI applications to enterprise systems and knowledge sources.
• Develop Retrieval-Augmented Generation (RAG), GraphRAG, and Knowledge Graph solutions for knowledge retrieval and semantic search.
• Develop scalable Python applications, APIs, and services to support AI and analytics use cases; work with SQL for data access.
• Perform data exploration, experimentation, testing, and performance optimization over structured and unstructured datasets.
• Create dashboards and reporting solutions to translate AI outputs into stakeholder-facing insights.
• Collaborate with Compliance, Technology, and Business stakeholders; contribute to reusable frameworks, engineering standards, testing practices, and AI governance.

Requirements

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related quantitative field.
• 5+ years of experience developing software, automation, analytics, or AI solutions.
• Strong programming skills in Python and SQL.
• Experience working with LLMs, Generative AI platforms, prompt engineering, and AI application development.
• Experience building solutions with orchestration frameworks such as LangGraph or LangChain (or similar).
• Understanding of Agentic AI concepts including tool calling, workflow automation, memory management, and multi-step reasoning.
• Experience implementing MCP (Model Context Protocol) integrations or similar enterprise integration patterns.
• Familiarity with RAG, embeddings, vector databases, semantic search, and knowledge retrieval techniques.
• Experience integrating with REST APIs and working with JSON.
• Strong problem-solving, analytical, and communication skills; ability to work independently and collaboratively.

Preferred Qualifications

• Experience with Neo4j, Knowledge Graphs, or GraphRAG architectures.
• Experience with AI observability, evaluation frameworks, and LLM testing methodologies.
• Experience with cloud-based AI platforms and enterprise AI ecosystems.
• Familiarity with compliance, risk management, or financial services domains.
• Experience building AI copilots, assistants, workflow automation solutions, or multi-agent systems.

LLMs Generative AI Agentic AI LangGraph Semantic Kernel LangChain MCP (Model Context Protocol) RAG GraphRAG Knowledge Graphs Python SQL Embeddings Vector Databases REST APIs JSON Neo4j

Skills

Problem Solving Analytical Thinking Communication Collaboration Software Development Experimentation Performance Optimization Prompt Engineering AI Governance Testing and Evaluation Systems Integration API Design Data Exploration